Whether This Participant will Attract You to This Event? Exploiting Participant Influence for Event Recommendation

Liao, Yi; Lin, Xinshi; Lam, Wai

doi:10.1109/icdm.2016.0132

Cited by 4 publications

(1 citation statement)

References 7 publications

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“…and found that communities in EBSNs are more cohesive than those in other types of social networks [29]. Many studies have proposed machine learning solutions for recommending events in EBSNs [25,32,33,41,48]. Most recently, Pramanik et al proposed an algorithm that can predict Meetup group success [46].…”

Section: Related Workmentioning

confidence: 99%

Analyzing Offline Social Engagements: An Empirical Study of Meetup Events Related to Software Development

Sharma¹,

Prana²,

Anamika³

et al. 2019

Preprint

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Software developers use a variety of social media channels and tools in order to keep themselves up to date, collaborate with other developers, and find projects to contribute to. Meetup is one of such social media used by software developers to organize community gatherings. Liu et al. characterized Meetup as an event-based social network (EBSN) which contains valuable offline social interactions in addition to online interactions. Recently, Storey et al. found out that Meetup was one of the social channels used by developers. We in this work investigate in detail the dynamics of Meetup groups and events related to software development, which has not been done in any of the previous works.In this work, we performed an empirical study of events and groups present on Meetup which are related to software development. First, we identified 6,317 Meetup groups related to software development and extracted 185,758 events organized by them. Then we took a statistically significant sample of 452 events (95% confidence level with 5% error margin) on which we performed open coding, based on which we were able to develop 9 categories of events (8 main categories +"Others"). Next, we did a popularity analysis of the categories of events and found that Talks by Domain Experts, Hands-on Sessions, and Open Discussions are the most popular categories of events organized by Meetup groups related to software development. Our findings show that more popular categories are those where developers can learn and gain knowledge. On doing a diversity analysis of Meetup groups we found 19.82% of the members on an average are female, which is a larger proportion as compared to numbers reported in previous studies on other social media. We also found that the groups related to technologies such as blockchain and machine learning have become more popular during last 5 years. We also built a topic association graph based on the topics. Our study results show that a lot of software community related information is present in Meetup data,

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